Laboratory for Advanced Power Systems (LAPS) research focuses on the utilization of new sensor technologies for operational and business support in the electrical grid.
Our research effort covers all layers of the data-to-application process. From different sources, traditional power network data is fused with external electrical market, weather, and geographical data. A suite of developed tools provides maximal information regarding the system state and expected evolution. Probabilistic as well as deterministic tools yield outputs such as renewable production estimates, outage probabilities, consumption patterns, etc. Applications developed for industrial partners implement the tool portfolio to address real world challenges faced by key players.
LAPS also provides an interface to the University energy management pilot to test applications at the low voltage levels and applications focused on energy conversion and distribution.
LAPS research effort can be split into several categories as follows:
- Decision support tools for ancillary services portfolio determination
- Optimization tools for purchase and activation of ancillary services considering balance as well as network security criteria
Renewable Energy Sources
- Modelling and prediction of renewable energy production
- Safe integration of renewables into power networks
Power Network Operation
- State Estimation Tools for Wide Area Monitoring Systems
- Dynamic Line Rating Methods
- Demand Side Management for Distribution Networks with High Share of Renewables
- Statistical analysis of power network operation including external influences and non-standard phenomena
Power Network Planning and Development
- Probabilistic modelling of network elements
- Stochastic power flow algorithms
- Security rating of distribution network
Predictive and Preventive Maintenance
- Optimization of maintenance plan for energy devices
- Stochastic modelling and simulation reliability of key power network elements
This page is temporary and provides only basic overview. For more details about LAPS, please contact Dr. Daniel Georgiev (email@example.com).